





from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig


UpperCAmelCase_							=				{
    'albert-base-v1': 'https://huggingface.co/albert-base-v1/resolve/main/config.json',
    'albert-large-v1': 'https://huggingface.co/albert-large-v1/resolve/main/config.json',
    'albert-xlarge-v1': 'https://huggingface.co/albert-xlarge-v1/resolve/main/config.json',
    'albert-xxlarge-v1': 'https://huggingface.co/albert-xxlarge-v1/resolve/main/config.json',
    'albert-base-v2': 'https://huggingface.co/albert-base-v2/resolve/main/config.json',
    'albert-large-v2': 'https://huggingface.co/albert-large-v2/resolve/main/config.json',
    'albert-xlarge-v2': 'https://huggingface.co/albert-xlarge-v2/resolve/main/config.json',
    'albert-xxlarge-v2': 'https://huggingface.co/albert-xxlarge-v2/resolve/main/config.json',
}
class     UpperCamelCase__					(     lowerCamelCase__				):






		'''simple docstring'''






		__a       :       Union[str, Any]       =	"""albert"""






		def __init__(							self,   snake_case__=3_00_00,   snake_case__=1_28,   snake_case__=40_96,   snake_case__=12,   snake_case__=1,   snake_case__=64,   snake_case__=1_63_84,   snake_case__=1,   snake_case__="gelu_new",   snake_case__=0,   snake_case__=0,   snake_case__=5_12,   snake_case__=2,   snake_case__=0.02,   snake_case__=1E-12,   snake_case__=0.1,   snake_case__="absolute",   snake_case__=0,   snake_case__=2,   snake_case__=3,   **snake_case__,   )       -> Optional[Any]:






									"""simple docstring"""
									super().__init__(pad_token_id=__snake_case,   bos_token_id=__snake_case,   eos_token_id=__snake_case,   **__snake_case  )

									lowercase_	:   Any  				=     vocab_size
									lowercase_	:   List[str]  				=     embedding_size
									lowercase_	:   Any  				=     hidden_size
									lowercase_	:   Union[str, Any]  				=     num_hidden_layers
									lowercase_	:   Optional[int]  				=     num_hidden_groups
									lowercase_	:   Tuple  				=     num_attention_heads
									lowercase_	:   Union[str, Any]  				=     inner_group_num
									lowercase_	:   List[Any]  				=     hidden_act
									lowercase_	:   Optional[Any]  				=     intermediate_size
									lowercase_	:   Any  				=     hidden_dropout_prob
									lowercase_	:   Any  				=     attention_probs_dropout_prob
									lowercase_	:   List[Any]  				=     max_position_embeddings
									lowercase_	:   Optional[int]  				=     type_vocab_size
									lowercase_	:   int  				=     initializer_range
									lowercase_	:   Tuple  				=     layer_norm_eps
									lowercase_	:   Optional[Any]  				=     classifier_dropout_prob
									lowercase_	:   List[str]  				=     position_embedding_type




class     UpperCamelCase__					(     lowerCamelCase__				):






		'''simple docstring'''






		@property
		def 						snake_case__				(							self  )       -> List[str]:






									"""simple docstring"""
									if self.task == "multiple-choice":
																lowercase_	:   Union[str, Any]  				=     {0: 'batch', 1: 'choice', 2: 'sequence'}
									else:
																lowercase_	:   Any  				=     {0: 'batch', 1: 'sequence'}
									return OrderedDict(
									    [
									        ("""input_ids""", dynamic_axis),
									        ("""attention_mask""", dynamic_axis),
									        ("""token_type_ids""", dynamic_axis),
									    ]  )




'''simple docstring'''






from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_torch_available,
)


lowerCAmelCase:   List[str]					=		{
    'configuration_falcon': ['FALCON_PRETRAINED_CONFIG_ARCHIVE_MAP', 'FalconConfig'],
}

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     lowerCAmelCase:   str					=		[
         'FALCON_PRETRAINED_MODEL_ARCHIVE_LIST',
         'FalconForCausalLM',
         'FalconModel',
         'FalconPreTrainedModel',
         'FalconForSequenceClassification',
         'FalconForTokenClassification',
         'FalconForQuestionAnswering',
     ]


if TYPE_CHECKING:
     from .configuration_falcon import FALCON_PRETRAINED_CONFIG_ARCHIVE_MAP, FalconConfig

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_falcon import (
              FALCON_PRETRAINED_MODEL_ARCHIVE_LIST,
              FalconForCausalLM,
              FalconForQuestionAnswering,
              FalconForSequenceClassification,
              FalconForTokenClassification,
              FalconModel,
              FalconPreTrainedModel,
          )


else:
     import sys

     lowerCAmelCase:   Optional[int]					=		_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)